Monday, August 5, 2013

Bye bye Java, Hello Scala

In the JVM world, Scala is certainly the rising star. Created at EPFL in 2001, its strongly gaining in popularity. Depending on the indices, it ranks now as a "serious" language reaching far beyond the academic world and adopted in mainstream companies (twitter backend, Ebay research, Netflix, FourSquare etc.).
For data scientists, this language is a breeze. Above the religion war between functional and object oriented believers, it succeeded by merging the best of both worlds, with a strong drive at "let's be practical."
If Grails/Groovy was a big step forwards in productivity on the JVM, Scala goes even further, mixing static typing (thus efficiency) with many improvements in the language structure, collections handling, concurrency, backed by solid frameworks and a very active community.
In this post, I'll picked up six major (and subjective) improvements, showing my hardcore Java colleagues how jumping on this train would be a promise of a great journey.

Sunday, January 20, 2013

Recently in a Scala project, I've hit a problem with sparse bit set. Typically, I was moving around set of 30~50 integers between 0 and 2047 with operation such as xor, and, circular shift etc. Basic operations, but repeated extensively, were soon to become a bottleneck in my application. The first implementation used scala BigInt (the main reason was the straightforwards shift call) but it later appeared that other solutions were more suited to the problem.
In this post, I will profile basic operation on 5 implementation alternatives: Scala BigInt, mutable and immutable BitSet versus Java BigInteger and BitSet (Java type can be used inside the Scala application of course).
Source code is available on github